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» A Very Fast Method for Clustering Big Text Datasets
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SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
14 years 11 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
AH
2008
Springer
15 years 4 months ago
Collection Browsing through Automatic Hierarchical Tagging
In order to navigate huge document collections efficiently, tagged hierarchical structures can be used. For users, it is important to correctly interpret tag combinations. In this ...
Korinna Bade, Marcel Hermkes
SDM
2012
SIAM
247views Data Mining» more  SDM 2012»
13 years 1 days ago
Simplex Distributions for Embedding Data Matrices over Time
Early stress recognition is of great relevance in precision plant protection. Pre-symptomatic water stress detection is of particular interest, ultimately helping to meet the chal...
Kristian Kersting, Mirwaes Wahabzada, Christoph R&...
DPD
2002
125views more  DPD 2002»
14 years 9 months ago
Parallel Mining of Outliers in Large Database
Data mining is a new, important and fast growing database application. Outlier (exception) detection is one kind of data mining, which can be applied in a variety of areas like mon...
Edward Hung, David Wai-Lok Cheung
BMCBI
2010
193views more  BMCBI 2010»
14 years 4 months ago
Mayday - integrative analytics for expression data
Background: DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the ge...
Florian Battke, Stephan Symons, Kay Nieselt